A method is presented to determine the acoustic masking effects of man-made
noise on marine mammal communication. In particular, the interference of
icebreaker related noise with beluga whale vocalizations is studied. Captive
beluga whales have been trained for acoustic experiments during which they try
to detect beluga vocalizations in various noisy backgrounds. In a stop/go
manner, the animals indicate whether or not they can discriminate call from
noise. Results are that bubbler system noise, generated when an icebreaker
ejects high pressure air into the sea in order to push ice debris away, has the
worst masking effects followed by propeller cavitation noise, generated when an
icebreaker is stopped by an iceridge. Naturally occurring thermal icecracking
noise has the least masking impact. Based on the experimentally collected data,
computer software was developed to model the whale's auditory abilities. Means
of adaptive noise cancellation greatly outperform the whale and are hence not
considered to take place in the whale's brain. A backpropagation neural network
showed the best similarity to the whale's performance and classified the noises
in the same order of disturbance as the whale.